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Neo-Luddism Critiquing Technology Dr. Julian Beckton
Aims ,[object Object],[object Object],[object Object],[object Object]
The Utilitarians ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
T “ The valley is gone and the Gods with it, and now, every fool in Buxton can be at Bakewell in half-an-hour, and every fool in Bakewell at Buxton; which you think a lucrative process of exchange – you fools everywhere.” (Ruskin, c1870)
Technology and education Have a look at this short video – pleading for more funding for Arizona’s e-learning programme, and list the ideas about e-learning inherent in it.
Software ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Information ,[object Object],[object Object],[object Object]
I have known the inexorable sadness of pencils, Neat in their boxes, dolor of pad and paper weight, All the misery of manila folders and mucilage, Desolation in immaculate public places, Lonely reception room, lavatory, switchboard, The unalterable pathos of basin and pitcher, Ritual of multigraph, paper-clip, comma, Endless duplication of lives and objects. And I have seen dust from the walls of institutions, Finer than flour, alive, more dangerous than silica, Sift, almost invisible, through long afternoons of tedium, Dropping a fine film on nails and delicate eyebrows, Glazing the pale hair, the duplicate grey standard faces.  Theodore Roethke Whose power? Power to do what? Power over whom? What is the source of information’s power?
Commodifying information ,[object Object],[object Object],[object Object],[object Object]
Would the existence of radio galaxies, quasars, pulsars, and the microwave background ever have been revealed if their discovery had depended on the computerised radio observations of today? The computers act as very narrow filters of information; they must be oriented to specific observations …i.e. what the observer expects to see (Lovell, 1984:94, quoted Roszak, 186:115)
Going out in the rain?
 
Strands of the Education Market ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Consequences ,[object Object],[object Object],[object Object]
How many computers have  YOU  got?
Part 2: Ways of ‘resistance’ ,[object Object],[object Object],[object Object],[object Object]
 
 
 
 
Slide Credits Monsal Dale  http://www.flickr.com/photos/dullhunk/3384945235/sizes/l/in/photostream/ Wottalottacomputers: http://www.flickr.com/photos/davidglover/3300194897/sizes/l/in/photostream/ Files1  http://www.flickr.com/photos/drpritch/4430561244/sizes/l/in/photostream/   Galaxy1  http://www.flickr.com/photos/neurokinetikz/273857131/sizes/l/in/photostream/   Rainypaper  http://www.flickr.com/photos/oaklandearthgirl/3597626469/sizes/l/in/photostream/   UCLA  http://www.flickr.com/photos/tatler/17940422/sizes/l/in/photostream/   Luddites  http://www.flickr.com/photos/johnnyg1955/3740823776/sizes/l/in/photostream/   Creative commons  http://thegoldguys.blogspot.com/   Wikipedia logo  http://upload.wikimedia.org/wikipedia/commons/thumb/8/80/Wikipedia-logo-v2.svg/2000px-Wikipedia-logo-v2.svg.png  (not for public release) Academic Commons.  http:// commons.gc.cuny.edu /
Oh, and one last thing! (just in case you thought I had something against using technology!
Slide 1-2 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 3-4 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 5 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 6-7 notes Slide 6 Most of what we do is actually informed by ideas not facts. Ideas are moral, immoral, ethical, or unethical right or wrong. But they’re never correct or incorrect. They depend on your point of view.  We place a great deal of emphasis on information, but to ignore the primacy of ideas is extremely risky. It is really how information is used that matters. Why do we gather the information that we do? For what purposes?  Slide 7 This is a metaphysical and epistemological question about the nature of knowledge. What does it mean to “know” something.  (In fact, let’s all share something that we know. Doesn’t matter what) That should have produced a random collection of facts. Yet, information is only useful if it has something in common with other bits of information. (e.g. people who live in postcode X buy lots more Jedward albums than people who live in postcode Y.  If we can do this, we can begin to make rational predictions about likely outcomes of interventions. But there’s still a moral dimension to our decisions.  There’s also a practical dimension. Why are we relating THESE bits of information to THOSE other bits of information?  Essentially, I’d argue, it’s because we’ve had an idea and we want to test it!
Slide 8-9 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 10-11 notes Slide 10 Bernard Lovell, Astronomer Royal was essentially making the obvious point that if you look at things from a particular perspective, you’re going to see things from that perspective. In other words, you find what you’re looking for.  It sometimes works the other way – Darwin’s theory of evolution came out of his observation of the shape of the beaks of different finch species and the idea that they needed to be different because of their environment. No computer could ever have worked that out though. For computers are, as Lovell suggests, narrow filters of information. There is not the slightest possibility of serendipitous discovery.  For that you need multiple sensory inputs – Think of Proust and his Madeleine cakes. -  We are miles and miles away from this kind of artificial intelligence. Slide 11 You want to read the paper. It’s out on the lawn (This is the USA) So you should go out and pick it up. Quite an easy decision to make, even with lots of information. You’d think wouldn’t you? But it’s raining. In which case you put on a coat. But it’s raining really hard. And you’ve just had your hair done. So you get an umbrella. But then you think, The newspaper’s going to be sopping wet anyway when I get it out of its wrapper. And I really don’t want to. So you turn on the radio… There’s ostensibly logical thinking in this, but a genuine research project At Berkeley University, described in Roszak pp124-125) failed to write a program to replicate it. The human mind doesn’t work that way – but it’s the only way a computer can do it.  The point is that you KNOW what to do. The machine doesn’t. Not that stops people trying to sell knowledge!
Slide 12-13 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 14-15 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 16-17 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 18 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 19-20 notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Slide 21 notes (summary)  ,[object Object],[object Object],[object Object]

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Neo luddism

  • 2.
  • 3.
  • 4. T “ The valley is gone and the Gods with it, and now, every fool in Buxton can be at Bakewell in half-an-hour, and every fool in Bakewell at Buxton; which you think a lucrative process of exchange – you fools everywhere.” (Ruskin, c1870)
  • 5. Technology and education Have a look at this short video – pleading for more funding for Arizona’s e-learning programme, and list the ideas about e-learning inherent in it.
  • 6.
  • 7.
  • 8. I have known the inexorable sadness of pencils, Neat in their boxes, dolor of pad and paper weight, All the misery of manila folders and mucilage, Desolation in immaculate public places, Lonely reception room, lavatory, switchboard, The unalterable pathos of basin and pitcher, Ritual of multigraph, paper-clip, comma, Endless duplication of lives and objects. And I have seen dust from the walls of institutions, Finer than flour, alive, more dangerous than silica, Sift, almost invisible, through long afternoons of tedium, Dropping a fine film on nails and delicate eyebrows, Glazing the pale hair, the duplicate grey standard faces. Theodore Roethke Whose power? Power to do what? Power over whom? What is the source of information’s power?
  • 9.
  • 10. Would the existence of radio galaxies, quasars, pulsars, and the microwave background ever have been revealed if their discovery had depended on the computerised radio observations of today? The computers act as very narrow filters of information; they must be oriented to specific observations …i.e. what the observer expects to see (Lovell, 1984:94, quoted Roszak, 186:115)
  • 11. Going out in the rain?
  • 12.  
  • 13.
  • 14.
  • 15. How many computers have YOU got?
  • 16.
  • 17.  
  • 18.  
  • 19.  
  • 20.  
  • 21. Slide Credits Monsal Dale http://www.flickr.com/photos/dullhunk/3384945235/sizes/l/in/photostream/ Wottalottacomputers: http://www.flickr.com/photos/davidglover/3300194897/sizes/l/in/photostream/ Files1 http://www.flickr.com/photos/drpritch/4430561244/sizes/l/in/photostream/ Galaxy1 http://www.flickr.com/photos/neurokinetikz/273857131/sizes/l/in/photostream/ Rainypaper http://www.flickr.com/photos/oaklandearthgirl/3597626469/sizes/l/in/photostream/ UCLA http://www.flickr.com/photos/tatler/17940422/sizes/l/in/photostream/ Luddites http://www.flickr.com/photos/johnnyg1955/3740823776/sizes/l/in/photostream/ Creative commons http://thegoldguys.blogspot.com/ Wikipedia logo http://upload.wikimedia.org/wikipedia/commons/thumb/8/80/Wikipedia-logo-v2.svg/2000px-Wikipedia-logo-v2.svg.png (not for public release) Academic Commons. http:// commons.gc.cuny.edu /
  • 22. Oh, and one last thing! (just in case you thought I had something against using technology!
  • 23.
  • 24.
  • 25.
  • 26. Slide 6-7 notes Slide 6 Most of what we do is actually informed by ideas not facts. Ideas are moral, immoral, ethical, or unethical right or wrong. But they’re never correct or incorrect. They depend on your point of view. We place a great deal of emphasis on information, but to ignore the primacy of ideas is extremely risky. It is really how information is used that matters. Why do we gather the information that we do? For what purposes? Slide 7 This is a metaphysical and epistemological question about the nature of knowledge. What does it mean to “know” something. (In fact, let’s all share something that we know. Doesn’t matter what) That should have produced a random collection of facts. Yet, information is only useful if it has something in common with other bits of information. (e.g. people who live in postcode X buy lots more Jedward albums than people who live in postcode Y. If we can do this, we can begin to make rational predictions about likely outcomes of interventions. But there’s still a moral dimension to our decisions. There’s also a practical dimension. Why are we relating THESE bits of information to THOSE other bits of information? Essentially, I’d argue, it’s because we’ve had an idea and we want to test it!
  • 27.
  • 28. Slide 10-11 notes Slide 10 Bernard Lovell, Astronomer Royal was essentially making the obvious point that if you look at things from a particular perspective, you’re going to see things from that perspective. In other words, you find what you’re looking for. It sometimes works the other way – Darwin’s theory of evolution came out of his observation of the shape of the beaks of different finch species and the idea that they needed to be different because of their environment. No computer could ever have worked that out though. For computers are, as Lovell suggests, narrow filters of information. There is not the slightest possibility of serendipitous discovery. For that you need multiple sensory inputs – Think of Proust and his Madeleine cakes. - We are miles and miles away from this kind of artificial intelligence. Slide 11 You want to read the paper. It’s out on the lawn (This is the USA) So you should go out and pick it up. Quite an easy decision to make, even with lots of information. You’d think wouldn’t you? But it’s raining. In which case you put on a coat. But it’s raining really hard. And you’ve just had your hair done. So you get an umbrella. But then you think, The newspaper’s going to be sopping wet anyway when I get it out of its wrapper. And I really don’t want to. So you turn on the radio… There’s ostensibly logical thinking in this, but a genuine research project At Berkeley University, described in Roszak pp124-125) failed to write a program to replicate it. The human mind doesn’t work that way – but it’s the only way a computer can do it. The point is that you KNOW what to do. The machine doesn’t. Not that stops people trying to sell knowledge!
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.

Editor's Notes

  1. .